Staff Applied Scientist

As a Staff Applied Scientist at Robin AI, your primary responsibilities will include leading research efforts in machine learning and AI aimed at solving challenges in the legal domain. You’ll be developing methods for understanding large language models, creating algorithms that enhance model transparency, and fine-tuning these models to work with diverse information architectures. Additionally, you will collaborate with teammates to communicate research findings internally and publicly, while keeping abreast of the latest advancements in the field.

To qualify for the Staff Applied Scientist role at Robin AI, candidates should ideally possess a Ph.D. in fields such as Computer Science, Data Science, or Machine Learning, although equivalent practical experience is also considered. Direct working experience with interpretability, personalization techniques, and large-scale data analytics is essential, while a strong background in machine learning algorithms and statistical methods is preferred. Moreover, a track record of scientific research and the ability to work in cross-disciplinary teams will be crucial.

At Robin AI, we prioritize career growth for our Staff Applied Scientists by promoting high performers and providing opportunities for progression. We foster a collaborative environment that encourages mentorship, allowing individuals to both teach and learn within our team. Alongside a culture of knowledge sharing and continuous improvement, we ensure that our scientists have access to resources and support to innovate and make a meaningful impact in the field.

The culture at Robin AI is dynamic, supportive, and grounded in creativity and resourcefulness. As a Staff Applied Scientist, you'll be part of a community that encourages pushing boundaries and exploring new ideas, where every team member has the freedom to take risks and navigate uncertainty. This environment fosters not just professional growth but personal fulfillment, as you work alongside passionate individuals dedicated to transforming the legal industry.

Staff Applied Scientists at Robin AI can expect a competitive salary, a generous equity package, and a flexible hybrid working schedule. We offer a robust health and wellbeing program, which includes comprehensive health insurance, mental healthcare support, gym discounts, and a cycle to work scheme. Additionally, our generous annual leave policy provides 25 days of PTO, plus UK bank holidays, ensuring a healthy work-life balance.

In answering this question, focus on specific projects you’ve worked on involving large language models. Explain the methodologies you employed, the challenges you faced, and the outcomes achieved. Highlight your understanding of the models' inner workings, as well as your strategies for enhancing their interpretability and personalizability to align with the goals of Robin AI.

When preparing to answer this question, outline your systematic approach to reverse engineering algorithms. Discuss the tools and techniques you have utilized, along with examples of insights gained and how those are applied in real-world scenarios, particularly within the legal AI domain, as this is relevant to the role.

For this question, discuss various techniques such as model interpretation tools, visualization methods, and approaches like LIME or SHAP. Describe how you can communicate findings effectively to stakeholders and why transparency is crucial, especially for clients relying on legal AI at Robin AI.

In answering this, provide a brief overview of the project and specific mentoring techniques you used. Discuss how you facilitated their learning, encouraged their contributions, and built a collaborative team dynamic. Highlight any successful outcomes resulting from their growth during the project.

Here, provide specific instances where reinforcement learning was applied in your work. Explain how you designed the learning environment, the reward mechanisms involved, and how you evaluated model performance. Connect these experiences to how they would be beneficial in the Staff Applied Scientist role at Robin AI.

Mention your strategies for staying informed, such as following key journals, attending conferences, or participating in relevant online forums. Discuss how you filter through information to find applicable insights that can drive innovation in your work at Robin AI.

In your answer, discuss specific algorithms you’ve worked with, providing examples of their applications in previous roles. Detail why you believe they are effective and how they apply to the goals of the Staff Applied Scientist position, particularly within the legal context.

Outline the challenge clearly, your approach to overcoming it, and the lessons learned. This shows resilience and problem-solving skills, qualities highly valued in a Staff Applied Scientist at Robin AI.

Discuss your philosophy on teamwork and provide examples of successful collaborations. Emphasize the importance of integrating diverse perspectives to enhance research quality and innovation, which is vital for Robins AI's mission.

Here, express your passion for the intersection of technology and the legal domain. Mention specific trends or innovations you find inspiring and how they relate to the mission of Robin AI, focusing on how you envision contributing to this evolving landscape.